Model-Based Predictive Detector of a Fire inside the Road Tunnel for Intelligent Vehicles
The paper proposes a method for detection of a fire inside the road tunnel without direct view on the fire, using on-board vehicle technologies. The system is based on comparing the measured development of temperature and smoke with model scenarios precomputed for a given road tunnel. The fire scena...
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| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2021-01-01
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| Series: | Journal of Advanced Transportation |
| Online Access: | http://dx.doi.org/10.1155/2021/6634944 |
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| _version_ | 1832568591295184896 |
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| author | Marián Hruboš Dušan Nemec Emília Bubeníková Peter Holečko Juraj Spalek Michal Mihálik Marek Bujňák Ján Andel Tomáš Tichý |
| author_facet | Marián Hruboš Dušan Nemec Emília Bubeníková Peter Holečko Juraj Spalek Michal Mihálik Marek Bujňák Ján Andel Tomáš Tichý |
| author_sort | Marián Hruboš |
| collection | DOAJ |
| description | The paper proposes a method for detection of a fire inside the road tunnel without direct view on the fire, using on-board vehicle technologies. The system is based on comparing the measured development of temperature and smoke with model scenarios precomputed for a given road tunnel. The fire scenarios are computed by HW/SW tool TuSim regarding the parameters of the real road tunnel and then the results are presented to the vehicles via car-to-infrastructure communication link. The proper detection of the fire allows early evacuation of the vehicle passengers, which will significantly increase chance of their survival. The computed scenarios also provide supporting information for the rescue teams. |
| format | Article |
| id | doaj-art-a7f0413728c740a0a0222b81488f2bb8 |
| institution | Kabale University |
| issn | 0197-6729 2042-3195 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Advanced Transportation |
| spelling | doaj-art-a7f0413728c740a0a0222b81488f2bb82025-02-03T00:58:49ZengWileyJournal of Advanced Transportation0197-67292042-31952021-01-01202110.1155/2021/66349446634944Model-Based Predictive Detector of a Fire inside the Road Tunnel for Intelligent VehiclesMarián Hruboš0Dušan Nemec1Emília Bubeníková2Peter Holečko3Juraj Spalek4Michal Mihálik5Marek Bujňák6Ján Andel7Tomáš Tichý8Department of Control and Information Systems, Faculty of Electrical Engineering and Information Technology, University of Žilina, Žilina, SlovakiaDepartment of Control and Information Systems, Faculty of Electrical Engineering and Information Technology, University of Žilina, Žilina, SlovakiaDepartment of Control and Information Systems, Faculty of Electrical Engineering and Information Technology, University of Žilina, Žilina, SlovakiaDepartment of Control and Information Systems, Faculty of Electrical Engineering and Information Technology, University of Žilina, Žilina, SlovakiaDepartment of Control and Information Systems, Faculty of Electrical Engineering and Information Technology, University of Žilina, Žilina, SlovakiaDepartment of Control and Information Systems, Faculty of Electrical Engineering and Information Technology, University of Žilina, Žilina, SlovakiaDepartment of Control and Information Systems, Faculty of Electrical Engineering and Information Technology, University of Žilina, Žilina, SlovakiaDepartment of Control and Information Systems, Faculty of Electrical Engineering and Information Technology, University of Žilina, Žilina, SlovakiaDepartment of Transport Telematics, Faculty of Transportation Scieneces, Czech Technical University, Prague, Czech RepublicThe paper proposes a method for detection of a fire inside the road tunnel without direct view on the fire, using on-board vehicle technologies. The system is based on comparing the measured development of temperature and smoke with model scenarios precomputed for a given road tunnel. The fire scenarios are computed by HW/SW tool TuSim regarding the parameters of the real road tunnel and then the results are presented to the vehicles via car-to-infrastructure communication link. The proper detection of the fire allows early evacuation of the vehicle passengers, which will significantly increase chance of their survival. The computed scenarios also provide supporting information for the rescue teams.http://dx.doi.org/10.1155/2021/6634944 |
| spellingShingle | Marián Hruboš Dušan Nemec Emília Bubeníková Peter Holečko Juraj Spalek Michal Mihálik Marek Bujňák Ján Andel Tomáš Tichý Model-Based Predictive Detector of a Fire inside the Road Tunnel for Intelligent Vehicles Journal of Advanced Transportation |
| title | Model-Based Predictive Detector of a Fire inside the Road Tunnel for Intelligent Vehicles |
| title_full | Model-Based Predictive Detector of a Fire inside the Road Tunnel for Intelligent Vehicles |
| title_fullStr | Model-Based Predictive Detector of a Fire inside the Road Tunnel for Intelligent Vehicles |
| title_full_unstemmed | Model-Based Predictive Detector of a Fire inside the Road Tunnel for Intelligent Vehicles |
| title_short | Model-Based Predictive Detector of a Fire inside the Road Tunnel for Intelligent Vehicles |
| title_sort | model based predictive detector of a fire inside the road tunnel for intelligent vehicles |
| url | http://dx.doi.org/10.1155/2021/6634944 |
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